Skip to content

Instantly share code, notes, and snippets.

@chewbranca
Created January 9, 2017 19:37
Show Gist options
  • Save chewbranca/3473a220c1a23854424a6f4183783f9f to your computer and use it in GitHub Desktop.
Save chewbranca/3473a220c1a23854424a6f4183783f9f to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib as plt\n",
"\n",
"%matplotlib inline\n",
"\n",
"np.random.seed(24)\n",
"df = pd.DataFrame({'A': np.linspace(1, 10, 10)})\n",
"df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],\n",
" axis=1)\n",
"df.iloc[0, 2] = np.nan\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x11cf684d0>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAECCAYAAADw0Rw8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11ce49c10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.plot.line(y=\"B\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style type=\"text/css\" >\n",
" \n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col0 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col1 {\n",
" \n",
" background-color: #188d18;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col2 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col3 {\n",
" \n",
" background-color: #c7eec7;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col4 {\n",
" \n",
" background-color: #a6dca6;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col0 {\n",
" \n",
" background-color: #ccf1cc;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col1 {\n",
" \n",
" background-color: #c0eac0;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col2 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col3 {\n",
" \n",
" background-color: #62b662;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col4 {\n",
" \n",
" background-color: #5cb35c;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col0 {\n",
" \n",
" background-color: #b3e3b3;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col1 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col2 {\n",
" \n",
" background-color: #56af56;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col3 {\n",
" \n",
" background-color: #56af56;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col4 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col0 {\n",
" \n",
" background-color: #99d599;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col1 {\n",
" \n",
" background-color: #329c32;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col2 {\n",
" \n",
" background-color: #5fb55f;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col3 {\n",
" \n",
" background-color: #daf9da;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col4 {\n",
" \n",
" background-color: #3ba13b;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col0 {\n",
" \n",
" background-color: #80c780;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col1 {\n",
" \n",
" background-color: #108910;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col2 {\n",
" \n",
" background-color: #0d870d;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col3 {\n",
" \n",
" background-color: #90d090;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col4 {\n",
" \n",
" background-color: #4fac4f;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col0 {\n",
" \n",
" background-color: #66b866;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col1 {\n",
" \n",
" background-color: #d2f4d2;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col2 {\n",
" \n",
" background-color: #389f38;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col3 {\n",
" \n",
" background-color: #048204;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col4 {\n",
" \n",
" background-color: #70be70;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col0 {\n",
" \n",
" background-color: #4daa4d;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col1 {\n",
" \n",
" background-color: #6cbc6c;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col2 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col3 {\n",
" \n",
" background-color: #a3daa3;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col4 {\n",
" \n",
" background-color: #0e880e;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col0 {\n",
" \n",
" background-color: #329c32;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col1 {\n",
" \n",
" background-color: #5cb35c;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col2 {\n",
" \n",
" background-color: #0e880e;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col3 {\n",
" \n",
" background-color: #cff3cf;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col4 {\n",
" \n",
" background-color: #4fac4f;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col0 {\n",
" \n",
" background-color: #198e19;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col1 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col2 {\n",
" \n",
" background-color: #dcfadc;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col3 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col4 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col0 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col1 {\n",
" \n",
" background-color: #7ec67e;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col2 {\n",
" \n",
" background-color: #319b31;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col3 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col4 {\n",
" \n",
" background-color: #5cb35c;\n",
" \n",
" }\n",
" \n",
" </style>\n",
"\n",
" <table id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" None>\n",
" \n",
"\n",
" <thead>\n",
" \n",
" <tr>\n",
" \n",
" <th class=\"blank\">\n",
" \n",
" <th class=\"col_heading level0 col0\">A\n",
" \n",
" <th class=\"col_heading level0 col1\">B\n",
" \n",
" <th class=\"col_heading level0 col2\">C\n",
" \n",
" <th class=\"col_heading level0 col3\">D\n",
" \n",
" <th class=\"col_heading level0 col4\">E\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row0\">\n",
" 0\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col0\" class=\"data row0 col0\">\n",
" 1\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col1\" class=\"data row0 col1\">\n",
" 1.32921\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col2\" class=\"data row0 col2\">\n",
" nan\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col3\" class=\"data row0 col3\">\n",
" -0.31628\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow0_col4\" class=\"data row0 col4\">\n",
" -0.99081\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row1\">\n",
" 1\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col0\" class=\"data row1 col0\">\n",
" 2\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col1\" class=\"data row1 col1\">\n",
" -1.07082\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col2\" class=\"data row1 col2\">\n",
" -1.43871\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col3\" class=\"data row1 col3\">\n",
" 0.564417\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow1_col4\" class=\"data row1 col4\">\n",
" 0.295722\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row2\">\n",
" 2\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col0\" class=\"data row2 col0\">\n",
" 3\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col1\" class=\"data row2 col1\">\n",
" -1.6264\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col2\" class=\"data row2 col2\">\n",
" 0.219565\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col3\" class=\"data row2 col3\">\n",
" 0.678805\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow2_col4\" class=\"data row2 col4\">\n",
" 1.88927\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row3\">\n",
" 3\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col0\" class=\"data row3 col0\">\n",
" 4\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col1\" class=\"data row3 col1\">\n",
" 0.961538\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col2\" class=\"data row3 col2\">\n",
" 0.104011\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col3\" class=\"data row3 col3\">\n",
" -0.481165\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow3_col4\" class=\"data row3 col4\">\n",
" 0.850229\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row4\">\n",
" 4\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col0\" class=\"data row4 col0\">\n",
" 5\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col1\" class=\"data row4 col1\">\n",
" 1.45342\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col2\" class=\"data row4 col2\">\n",
" 1.05774\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col3\" class=\"data row4 col3\">\n",
" 0.165562\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow4_col4\" class=\"data row4 col4\">\n",
" 0.515018\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row5\">\n",
" 5\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col0\" class=\"data row5 col0\">\n",
" 6\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col1\" class=\"data row5 col1\">\n",
" -1.33694\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col2\" class=\"data row5 col2\">\n",
" 0.562861\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col3\" class=\"data row5 col3\">\n",
" 1.39285\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow5_col4\" class=\"data row5 col4\">\n",
" -0.063328\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row6\">\n",
" 6\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col0\" class=\"data row6 col0\">\n",
" 7\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col1\" class=\"data row6 col1\">\n",
" 0.121668\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col2\" class=\"data row6 col2\">\n",
" 1.2076\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col3\" class=\"data row6 col3\">\n",
" -0.00204021\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow6_col4\" class=\"data row6 col4\">\n",
" 1.6278\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row7\">\n",
" 7\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col0\" class=\"data row7 col0\">\n",
" 8\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col1\" class=\"data row7 col1\">\n",
" 0.354493\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col2\" class=\"data row7 col2\">\n",
" 1.03753\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col3\" class=\"data row7 col3\">\n",
" -0.385684\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow7_col4\" class=\"data row7 col4\">\n",
" 0.519818\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row8\">\n",
" 8\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col0\" class=\"data row8 col0\">\n",
" 9\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col1\" class=\"data row8 col1\">\n",
" 1.68658\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col2\" class=\"data row8 col2\">\n",
" -1.32596\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col3\" class=\"data row8 col3\">\n",
" 1.42898\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow8_col4\" class=\"data row8 col4\">\n",
" -2.08935\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aad\" class=\"row_heading level4 row9\">\n",
" 9\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col0\" class=\"data row9 col0\">\n",
" 10\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col1\" class=\"data row9 col1\">\n",
" -0.12982\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col2\" class=\"data row9 col2\">\n",
" 0.631523\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col3\" class=\"data row9 col3\">\n",
" -0.586538\n",
" \n",
" <td id=\"T_00f0c328_d6a3_11e6_99ff_acbc32c50aadrow9_col4\" class=\"data row9 col4\">\n",
" 0.29072\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x11cafc3d0>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import seaborn as sns\n",
"\n",
"cm = sns.light_palette(\"green\", as_cmap=True)\n",
"\n",
"s = df.style.background_gradient(cmap=cm)\n",
"s\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x11d5fe150>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAECCAYAAADw0Rw8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11c392490>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.plot.line(y=\"B\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment